diff --git a/examples/tsodyksmarkramstp/tmevaluator.py b/examples/tsodyksmarkramstp/tmevaluator.py
index 6af53f88..db08bb75 100644
--- a/examples/tsodyksmarkramstp/tmevaluator.py
+++ b/examples/tsodyksmarkramstp/tmevaluator.py
@@ -4,10 +4,11 @@
 
 @author: Giuseppe Chindemi
 @remark: Copyright (c) 2017, EPFL/Blue Brain Project
-         This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
-         This library is free software; you can redistribute it and/or modify it
-         under the terms of the GNU Lesser General Public License version 3.0 as
-         published by the Free Software Foundation.
+         This file is part of BluePyOpt
+         <https://github.com/BlueBrain/BluePyOpt>
+         This library is free software; you can redistribute it and/or modify
+         it under the terms of the GNU Lesser General Public License version
+         3.0 as published by the Free Software Foundation.
          This library is distributed in the hope that it will be useful, but
          WITHOUT ANY WARRANTY; without even the implied warranty of
          MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
@@ -48,27 +49,27 @@ def __init__(self, t, v, tstim, params):
         self.stimidx = np.searchsorted(t, tstim)
         self.dx = t[1] - t[0]
         self.nsamples = len(v)
-        self.params = params
         # Find voltage baseline
         bs_stop = np.searchsorted(t, tstim[0])
         self.vrest = np.mean(v[:bs_stop])
         # Compute time windows where to compare model and data
         offset = 0.005  # s
         window = 0.04  # s
-        window_samples = int(np.round(window/self.dx))
-        psp_start = np.searchsorted(t, tstim+offset)
+        window_samples = int(np.round(window / self.dx))
+        psp_start = np.searchsorted(t, tstim + offset)
         psp_stop = psp_start + window_samples
-        psp_stop[-1] += 2*window_samples  # Extend last psp window (RTR case)
+        psp_stop[-1] += 2 * window_samples  # Extend last psp window (RTR case)
         self.split_idx = list(zip(psp_start, psp_stop))
         # Parameters to be optimized
         self.params = [bpop.parameters.Parameter(name, bounds=(minval, maxval))
-                       for name, minval, maxval in self.params]
+                       for name, minval, maxval in params]
         # Objectives
         self.objectives = [bpop.objectives.Objective('interval_%d' % (i,))
                            for i in xrange(len(self.split_idx))]
 
     def generate_model(self, individual):
-        """Calls numerical integrator `tmodeint.py` and returns voltage trace based on the input parameters"""
+        """Calls numerical integrator `tmodeint.py` and returns voltage trace
+        based on the input parameters"""
 
         v, _ = tmodeint.integrate(self.stimidx, self.nsamples, self.dx,
                                   self.vrest, *individual)